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RESEARCH AND CONCEPTS

The integration of lean management and Six Sigma Edward D. Arnheiter and John Maleyeff

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Lally School of Management & Technology, Rensselaer Polytechnic Institute, Hartford, Connecticut, USA Abstract Purpose – To eliminate many misconceptions regarding Six Sigma and lean management by describing each system and the key concepts and techniques that underlie their implementation. This discussion is followed by a description of what lean organizations can gain from Six Sigma and what Six Sigma organizations can gain from lean management. Design/methodology/approach – Comparative study of Six Sigma and lean management using available literature, critical analysis, and knowledge and professional experience of the authors. Findings – The joint implementation of the programs will result in a lean, Six Sigma (LSS) organization, overcoming the limitations of each program when implemented in isolation. A thorough analysis of the two programs provides some likely reasons why the programs alone may fail to achieve absolute perfection. Practical implications – A lean, Six Sigma (LSS) organization would capitalize on the strengths of both lean management and Six Sigma. An LSS organization would include three primary tenets of lean management, and the LSS organization would include three primary tenets of Six Sigma. Originality/value – Suggestions are made regarding concepts and methods that would constitute a lean, Six Sigma organization. Figures summarize the nature of improvements that may occur in organizations that practice lean management or Six Sigma, and the corresponding improvements that an integrated program could offer. Keywords Quality programmes, Just in time, Total quality management, Manufacturing systems Paper type Conceptual paper

Introduction Over the last two decades, American industrial organizations have embraced a wide variety of management programs that they hope will enhance competitiveness. Currently, two of the most popular programs are Six Sigma and lean management. Six Sigma was founded by Motorola Corporation and subsequently adopted by many US companies, including GE and Allied Signal. Lean management originated at Toyota in Japan and has been implemented by many major US firms, including Danaher Corporation and Harley-Davidson. Six Sigma and lean management have diverse roots. The key issue driving the development of Six Sigma was the need for quality improvement when manufacturing complex products having a large number of components, which often resulted in a correspondingly high probability of defective final products. The driving force behind the development of lean management was the elimination of waste, especially in Japan, a country with few natural resources. Both Six Sigma and lean management have evolved into comprehensive management systems. In each case, their effective implementation involves cultural changes in organizations, new approaches to production and to servicing customers,

The TQM Magazine Vol. 17 No. 1, 2005 pp. 5-18 q Emerald Group Publishing Limited 0954-478X DOI 10.1108/09544780510573020

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and a high degree of training and education of employees, from upper management to the shop floor. As such, both systems have come to encompass common features, such as an emphasis on customer satisfaction, high quality, and comprehensive employee training and empowerment. With disparate roots but similar goals, Six Sigma and lean management are both effective on their own. However, some organizations that have embraced either Six Sigma or lean management might find that they eventually reach a point of diminishing returns. That is, after re-engineering their operating and supporting systems for improvement by solving major problems and resolving key inefficiencies, further improvements are not easily generated, as illustrated in Figure 1. These organizations have begun to look elsewhere for sources of competitive advantage. Naturally, lean organizations are examining Six Sigma and Six Sigma organizations are exploring lean management. The term lean Sigma has recently been used to describe a management system that combines the two systems (Sheridan, 2000). In this paper, the term lean, Six Sigma (LSS) organization will be used to describe an entity that integrates the two systems. The purpose of this paper is to eliminate many misconceptions regarding Six Sigma and lean management by describing each system and the key concepts and techniques that underlie their implementation. Since these misconceptions may tend to discourage the education necessary for proponents of one system to become educated into the key elements of the other system, the misconceptions will be addressed one-by-one. This discussion will be followed by a description of what lean organizations can gain from Six Sigma and what Six Sigma organizations can gain from lean management. Finally, some suggestions will be made regarding concepts and methods that would constitute a lean, Six Sigma organization. Overview of Six Sigma The roots of Six Sigma can be traced to two primary sources: total quality management (TQM) and the Six-Sigma statistical metric originating at Motorola Corporation. Today, Six Sigma is a broad long-term decision-making business strategy rather than a narrowly focused quality management program. From TQM, Six Sigma preserved the concept that everyone in an organization is responsible for the quality of goods and services produced by the organization. Other components of Six Sigma that can be traced to TQM include the focus on customer

Figure 1. Improvements over time with Six Sigma or lean management alone

satisfaction when making management decisions, and a significant investment in education and training in statistics, root cause analysis, and other problem solving methodologies. With TQM, quality was the first priority. The main tools of TQM included the seven tools of quality: control charts, histograms, check sheets, scatter plots, cause-and-effect diagrams, flowcharts, and Pareto charts; and the seven management tools of quality: affinity diagrams, interrelationship digraphs, tree diagrams, matrix diagrams, prioritization matrices, process decision program charts, and activity network diagrams (Sower et al., 1999). The six-sigma metric was developed at Motorola in 1987 in response to sub-standard product quality traced in many cases to decisions made by engineers when designing component parts. Traditionally, design engineers used the “three-sigma” rule when evaluating whether or not an acceptable proportion of manufactured components would be expected to meet tolerances. When a component’s tolerances were consistent with a spread of six standard deviation units of process variation, about 99.7 percent of the components for a centered process would be expected to conform to tolerances. That is, only 0.3 percent of parts would be nonconforming to tolerances, which translates to about 3,000 non-conforming parts per million (NCPPM). At Motorola, as products became more complex, defective products were becoming more commonplace while at the same time customers were demanding higher quality. For example, a pager or cell phone included hundreds of components. Each component typically included numerous important quality characteristics. It was not uncommon for a product to include thousands of opportunities for defects (OFDs) in each product sold (Harry and Schroeder, 2000). Traditional three-sigma quality for each OFD was no longer acceptable. For example, consider a product that contains 1,000 OFDs. If, for each OFD, three-sigma quality levels are achieved, only about 5 percent of the products would be defect free. The calculation used to obtain this probability requires raising the fraction conforming (0.997) to the power of 1,000, and is based on the binomial probability distribution (Devore, 2000). The formula used to determine the probability of defect-free products provides only an approximate guideline for two reasons. Since three-sigma is the minimum design standard, it would be expected that many products would surpass the three-sigma standard. On the other hand, the 0.997 conformance probability assumes a centered process and it would be expected that many processes would not be centered every time a component is produced. The calculation does, however, effectively illustrate the challenge inherent in producing defect-free products. Assuming 1,000 OFDs, only 37 percent of products will be free of defects if the quality level at each OFD averaged 99.9 percent, and 90 percent of products will be free of defects if the quality level at each OFD averaged 99.99 percent. Other industries face similar challenges in achieving superior quality. In addition to the consumer electronics industry, other products with a large number of OFDs include automobiles, engines, airframes, and computers. Many industries where products are less complex also face similar challenges. Manufacturers of medical devices and other products where defects in the field may cause harm must achieve almost perfect quality. Companies that manufacture less complex products but sell them in very large volumes also need to be focused on achieving superior quality. At Motorola, when studying the relationship between component quality and final product quality it was discovered that, from lot-to-lot, a process tended to shift a

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maximum of 1.5 sigma units (McFadden, 1993). This concept is shown graphically in Figure 2, which shows a centered process and processes shifted 1.5 sigma units in both directions. Table I provides the relationship between component quality and final product quality, assuming that the full 1.5 sigma shift takes place. In Table I, Sigma level is the standardized process variation (see Figure 2), OFD quality is the NCPPM if the process shifts a full 1.5 sigma units, and the probabilities in the table provide the proportion of final products that will be free of defects. For example, if the company sets a goal for final product quality of 99.7 percent and products include about 1,000 OFDs, then the 3.4 NCPPM corresponding to the Six-Sigma metric would became the standard against which all decisions were made. In late 1999, Ford Motor Company became the first major automaker to adopt a Six Sigma strategy. At Ford, each car has approximately 20,000 OFDs. Therefore, if Ford were to attain Six Sigma quality, approximately one car in every 15 produced would contain a defect (Truby, 2000). It is interesting to note in Table I that if Ford operated at a 5.5 sigma level, about 50 percent of their cars would include at least one defect.

Figure 2. Process average shifting ^1.5 Sigma units

Sigma level

Table I. Final product quality level (percentage conforming)

2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5

OFD quality (NCPPM)

100 (%)

158,655 66,807 22,750 6,210 1,350 233 32 3.4 0.29 0.019 0.0010

0.0 0.1 10.0 53.6 87.4 97.7 99.7 100.0 100.0 100.0 100.0

Number of OFDs per product 500 1,000 5,000 (%) (%) (%)

20,000 (%)

0.0 0.0 0.0 4.4 50.9 89.0 98.4 99.8 100.0 100.0 100.0

0.0 0.0 0.0 0.0 0.0 1.0 53.1 93.4 99.4 100.0 100.0

0.0 0.0 0.0 0.2 25.9 79.2 96.9 99.7 100.0 100.0 100.0

0.0 0.0 0.0 0.0 0.1 31.2 85.3 98.3 99.9 100.0 100.0

Today, Six Sigma is a combination of the Six-Sigma statistical metric and TQM, with additional innovations that enhance the program’s effectiveness while expanding its focus. The main components of Six Sigma retained from TQM include a focus on the customer, recognition that quality is the responsibility of all employees, and the emphasis on employee training. The Six-Sigma metric is also used, but in an expanded fashion. With Six Sigma, the value of an organization’s output includes not just quality, but availability, reliability, delivery performance, and after-market service. Performance within each of the components of the customer’s value equation should be superior. Hence, the Six-Sigma metric is applied in a broad fashion, striving for near perfect performance at the lowest level of activity. In addition, Six Sigma programs generally create a structure under which training of employees is formalized and supported to ensure its effectiveness. All employees involved in activities that impact customer satisfaction would be trained in basic problem solving skills. Other employees are provided advanced training and required to act as mentors to others in support of quality improvement projects. Overview of lean management The concept of lean management can be traced to the Toyota production system (TPS), a manufacturing philosophy pioneered by the Japanese engineers Taiichi Ohno and Shigeo Shingo (Inman, 1999). It is well known, however, that Henry Ford achieved high throughput and low inventories, and practiced short-cycle manufacturing as early as the late 1910s. Ohno greatly admired and studied Ford because of his accomplishments and the overall reduction of waste at early Ford assembly plants (Hopp and Spearman, 2001). The TPS is also credited with being the birthplace of just-in-time (JIT) production methods, a key element of lean production, and for this reason the TPS remains a model of excellence for advocates of lean management. By contrast, the traditional US production system was based on the “batch-and-queue” concept. High production volumes, large batch sizes, and long non-value added queue times between operations characterize batch-and-queue production. Batch-and-queue techniques developed from economy of scale principles, which implicitly assumed that setup and changeover penalties make small batch sizes uneconomical. These methods typically result in lower quality since defects are usually not discovered until subsequent operations or in the finished product. Lean management emphasizes small batch sizes and, ultimately, single-piece flow (i.e. transfer batch size ¼ 1). The term pull is used to imply that nothing is made until it is needed by the downstream customer, and the application of a make-to-order (MTO) approach whenever possible. In some industries, such as the personal computer business, MTO production has become the de facto business model. The Dell “direct sales model”, for example, quickly converts customer orders into finished personal computers ready for shipment (Sheridan, 1999). The initial “pull” on the Dell production line is the telephone or electronic order from the customer. The direct sales model also allows Dell to customize each unit to the customer’s specifications. The lean production goal of eliminating waste (muda in Japanese), so that all activities along the value stream create value, is known as perfection. Efforts focused on the reduction of waste are pursued through continuous improvement or kaizen events, as well as radical improvement activities, or kaikaku. Both kaizen and kaikaku reduce muda, although the term kaikaku is generally reserved for the initial rethinking

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of a process. Hence, perfection is the goal and the journey to perfection is never ending (Womack and Jones, 1996). Another element of lean management is the reduction of variability at every opportunity, including demand variability, manufacturing variability, and supplier variability. Manufacturing variability includes not only variation of product quality characteristics (e.g. length, width, weight), but also variation present in task times (e.g. downtime, absenteeism, operator skill levels). Lean management attempts to reduce task time variation by establishing standardized work procedures. Supplier variability includes uncertainties in quality and delivery times. The reduction in supplier variability is often achieved through partnerships and other forms of supplier-producer cooperation. Lean production practices will often reduce lead times so drastically that it becomes feasible to practice MTO production, and still provide on-time deliveries. Even when a make-to-stock (MTS) approach is required (e.g. a high-volume consumer products company filling large supply and distribution channels), reducing lead times improves replenishment times, thereby lowering inventories throughout the supply network, and making the supply chain more respondent to demand uncertainties. It should be mentioned that individual processes do exist for which batch-and-queue systems are still currently necessary. This is often the case when performing operations such as chrome plating, where large batches are placed in plating tanks. In wrench manufacturing, for example, steel forgings might move in a single-piece flow through a U-shaped machining cell, but then accumulate into a large batch at the end of the cell before being moved to a chrome plating station. In fact, very few lean manufacturers have pure single-piece-flow systems throughout their entire operation. Lean management also applies to indirect and overhead activities. Any policy or procedure having a goal of optimizing the performance of a single portion of a company risks violating lean management rules. For example, a purchasing manager who is given a reward for cutting costs of component parts may sacrifice quality to achieve his or her goal. Accounting systems that measure efficiency of output for individuals or departments may encourage the generation of products when no demand exists. Quality management practices in lean production emphasize the concept of zero quality control (ZQC). A ZQC system includes mistake proofing (poka-yoke), source inspection (operators checking their own work), automated 100 percent inspection, stopping operations instantly when a mistake is made, and ensuring setup quality (Shingo, 1986). Typically, inspections are performed quickly using go-no go gages rather than more time consuming variable measurement methods. Quality practices in batch-and-queue generally emphasize acceptance sampling performed by dedicated inspectors, product quality audits, and statistical process control (SPC). Thus, for equivalent process quality levels, poor quality in a batch-and-queue system would result in high external failure costs, whereas poor quality in a lean production system would cause high internal failure costs (see Figure 3). Misconceptions regarding lean management and Six Sigma It is clear that lean management and Six Sigma were derived from two different points of view. Lean production was derived from the need to increase product flow velocity

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Figure 3. Batch-and-queue versus lean quality systems

through the elimination of all non value-added activities. Six Sigma developed from the need to ensure final product quality by focusing on obtaining very high conformance at the OFD level. In order for proponents of one program to learn from the other program, some common misconceptions should be dispelled. The key misconceptions are described below. Key misconceptions regarding lean management The most common misconception of lean management is lean means layoffs. While this misconception may be due to the term “lean” (especially in the context of “lean and mean”), it is a mis-interpretation of the term. In lean management, if an employee were performing non-value-added activities within their job, management and the employee would work together to find a better way to perform the job to eliminate the non-value-added activities. Laying-off the employee would be counterproductive since a knowledgeable person would no longer be available and the remaining employees would be reluctant to take part in future waste elimination projects. Hence, layoffs cannot take place in the context of lean management, unless it becomes an absolute necessity and every effort to re-assign or re-train the employee fails (Emiliani, 2001). Another misconception is that lean only works in Japan, because of their unique culture. This view is unsubstantiated. In fact, lean management is not a universal system in Japan and some of the most successful lean management implementations have been within non-Japanese companies (Emiliani, 2003). The source of the misconception may be the belief that Japanese workers are by nature more frugal than their international counterparts. Even if this statement were true, eliminating waste and being frugal often conflict, such as when an engineer designs an inferior part to save money. Another key misconception is that lean is for manufacturing only. Even in a manufacturing environment, lean management views each step in the process as a service step, where customer value is added with minimal waste. Within this framework, processing claims in the insurance industry, evaluating loan applications at a bank, and treating patients in a hospital all involve performing activities synonymous with the lean management viewpoint. In any business where customers

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exist and activities take place to satisfy those customers, lean management can be practiced successfully. A final misconception is that lean only works within certain environments. This view is heard from managers in operations that are traditionally large batch operations as well as from managers of diverse job-shop operations. While these types of operations may never conform to the “lot size of one” principle, lean management encompasses much more than manufacturing process design. If attempts were made to identify and eliminate all non-value-added activities throughout the organization, these companies would be practicing important aspects of lean management. These companies could also pursue other elements of lean management, by continuously attempting to follow lean principles when adopting new manufacturing technologies. For example, new technologies have become available that allow for small lot sizes on processes that traditionally require long setup or cycle times, including semi-conductor wafer cleaning (Lester, 2000), coating/laminating (Friedman, 2000), and chemical testing (Anne´, 2000). Key misconceptions regarding Six Sigma The most common misconception of Six Sigma is that it is the new flavor of the month, pushed by quality consultants in a way similar to the way Deming Management, TQM, business process reengineering (BPR), and ISO 9000 were pushed in the recent past. Unfortunately, there will always be consultants who jump onto any bandwagon, take a seminar and proclaim themselves experts in a program. Six Sigma is no exception to this phenomenon. However, Six Sigma should be considered state-of-the-art in terms of quality management, in that it borrows from previous programs, especially Deming’s management philosophies and TQM’s focus on the customer, and adds new features such as a comprehensive training structure and a broad definition of value from a customer’s perspective to include not only quality, but service and delivery. It is fair to say that while the name of Six Sigma may change in the future, the main features will be carried over to subsequent programs and new and improved versions will emerge. Another misconception of Six Sigma is that the goal of 3.4 NCPPM is absolute and should be applied to every opportunity tolerance and specification, regardless of its ultimate importance in the customer’s value expression. While the 3.4 NCPPM was derived at Motorola based on the characteristics of its products, Six Sigma programs do not use this metric as an absolute goal in all cases. As part of Six Sigma, the Pareto principle is applied so that improvement projects will focus on the “lowest hanging apple” and make improvements where they matter the most. Since no company’s business remains static very long, new products and services will generally provide a never-ending source of low hanging apples. Alternatively, examples can be found where a goal of 3.4 NCPPM will never be good enough and the target must be set at a higher sigma level. For example, the nuclear power, medical device, and aerospace industries all require the pursuit of exceptional quality to prevent catastrophic loss of human life. As a related point, proponents of ZQC systems may conclude that ZQC is preferred to Six Sigma given that ZQC results in zero NCPPM rather than “settling” for 3.4 NCPPM. This point is invalid for two reasons. First, as shown in Figure 4, the six-sigma metric is applied to the output from a process, before inspection takes place. The “zero” in the ZQC system applies to output from processes after an inspection

takes place. Second, many inspection systems are prone to inspection errors. Studies have shown that some inspection systems pass non-conforming items at alarming rates. These inspection errors will be especially prevalent on sensory inspections. For example, a study at an automotive manufacturer found that trained inspectors passed 73 percent of non-conforming items based on a sensory inspection (Burke et al., 1995). Hence, ZQC does not necessarily mean zero defects escaping the inspection. A final misconception of Six Sigma is that it is a quality only program. As described earlier, the concept of Six Sigma “quality” relates to the entire customer value equation. Its applicability is broad, encompassing manufacturing, delivery, service, and maintenance components.

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Integrating lean management and Six Sigma It was pointed out earlier that companies practicing either lean management or Six Sigma alone might reach a point of diminishing returns. In this section, benefits that may be derived by combining the programs are described. In addition, recommendations are made that will help companies practicing one of the programs to integrate the programs via evolutionary, rather than revolutionary, changes. What can lean organizations gain from Six Sigma? Lean organizations should make more use of data in decision-making and use methodologies that promote a more scientific approach to quality. For example, when quality problems occur within a lean management system, defects are likely to be identified internally via the ZQC system. When this occurs, waste is incurred in a number of ways. First, there is a loss of opportunity for the production of that component since operation times are synchronized with demand via the pull system of production control. Second, cost is added through rework or scrap. Third, indirect personnel and other overhead must be available to handle the scrap and rework, such as a repair department. As an example, consider a manufacturing cell with a two-minute cycle time. The cell operates for two eight-hour shifts, resulting in a target production of 480 units per day. Work in the cell consists of 20 individual tasks, and each unit of product possesses a total of 100 OFDs. In this cell, when the 480-unit daily target is not met due to system variations (e.g. defects, machine downtime, power failures), overtime must be utilized. Table II lists the average number of overtime hours that would need to be scheduled per day to accommodate the quality level noted. For example, if component quality at the OFD level were 1,000 NCPPM (0.1 percent), then on average 1.5 hours of overtime

Figure 4. Typical measurement points in the Six-Sigma and ZQC philosophies

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would be required per day. If this were the case, the company could allow for buffer quantities to be pre-produced, but this practice also creates waste and is undesirable. The ZQC system also has the potential to cause reliability and quality problems due to the interaction of tolerances in complex products. An example involving Ford transmissions illustrates the problem caused by relying on tolerance-based pass/fail criteria during inspections. Ford had a problem with warranty claims for automatic transmissions. The transmissions were made at both the Ford Batavia (Ohio, USA) facility and at a Mazda facility in Japan. Data showed that customer satisfaction was higher for the Mazda-built transmissions. Subsequently, samples of both Ford and Mazda transmissions were disassembled and each component part was measured (Gunter, 1987). The Ford transmissions all conformed to tolerances, but exhibited a much higher level of dimensional variation than the Mazda transmissions. With a product as complex as a transmission, the interaction of the parts caused more failures in the Ford transmissions. In order for a lean producer to ensure that this problem is not repeated, less dependence would need to be placed on pass/fail attribute inspections and more on keeping processes on target. The Ford transmission example illustrates a phenomenon that is likely to occur whenever attribute, or go-no go, inspections are used to judge quality, as is often the case in ZQC systems. By collecting and analyzing variable measurements using control charting methods, processes can be effectively kept on target. In cases where variable measurements are costly or time consuming, narrow limit gauging may be used to keep processes on target (Ott and Schilling, 1990). Alternatively, pre-control, also known as stoplight control, may be used within the context of ZQC (Salvia, 1988). A comparison of control charts and pre-control shows that under most conditions, control charts are better suited for keeping processes on target (Maleyeff and Lewis, 1993). What can Six Sigma companies gain from lean management? A competitive company must have both high quality goods and provide a high quality of service. For example, a company that operates in a batch-and-queue mode runs the risk of providing poor service to customers even if quality is at six sigma levels. By reducing manufacturing lead times, a company that is producing to order will enhance competitiveness by achieving faster deliveries or by meeting promised due dates a higher proportion of the time. A company that is producing to stock will gain from reduced lead times by decreasing the horizon of their forecasts and by replenishing stocks more often, thereby increasing the company’s revenues and inventory turnover rate. Six Sigma organizations should include training in lean management methods that eliminate all forms of waste, such as kaizen, reducing setup times, and mapping

Sigma level

Table II. Average number of overtime hours versus quality levels

3.8 4.6 5.2 5.8 6.0 6.3

OFD-level quality (NCPPM)

Percentage defect-free products

Average overtime hours/day

10,000 1,000 100 10 3.4 1

36.60 90.48 99.01 99.90 99.97 99.99

10.1 1.5 0.2 0.0 0.0 0.0

the value stream. Two examples will be used to show how Six Sigma organizations may get to a point of diminishing returns (illustrated in Figure 1), due to the non-use of certain lean management methodologies. Consider the following scenario, adapted from a Harvard Business School case study (Wong and Hammond, 1991). A manufacturing company that includes a children’s knitwear division is using a process-oriented layout (i.e. the plant is organized by machine type). For this product, the average number of operations is ten and the average processing time per operation is one minute. Like many companies run in this traditional batch-and-queue mode, processing is done in batches since machine setup times and the reluctance to risk idle machinery cause the company to accumulate large WIP inventories on the shop floor. In the case, it is noted that an average of 30,000 garments of work-in-process inventory exists on the shop floor and the average manufacturing lead time is 15 days. The 15-day lead time results in a percent value added time of 0.14 percent. Table III shows that, by reducing WIP inventory, thereby increasing the proportion of value-added time, the lead time can be reduced dramatically. For example, the lead time can be reduced to 17 hours by increasing the value added proportion to just 1 percent. It is within lean management that Six Sigma organizations will learn how to increase the value added time of their operations. Consider an alternative example involving a typical Six Sigma improvement project where an organization is experiencing too many missed due dates. Efforts to address the problem might begin with the “Five whys” root cause analysis, an approach also often practiced in a lean organization. The result of the “Five whys” series of questions are: (1) Problem is missing due dates – why? (2) Lead time are long – why? (3) Not enough capacity – why? (4) Long setup times – why? (5) Die adjustment is time consuming.

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At this point, two types of decisions are possible: (1) increase capacity by purchasing additional machinery, and (2) increase capacity by reducing the setup times. The latter alternative is preferable in terms of cost and would be the obvious choice in a lean organization. In this case, the real root cause in this situation may be that the lack of lean production knowledge within the organization has perpetuated and institutionalized long setup times. Percent value added time 0.14 0.5 1 5 10 25

Lead time (hours)

Lead time (days)

119.9 33.3 16.7 3.3 1.7 0.7

15.0 4.2 2.1 0.4 0.2 0.1

Table III. Effect of per cent value-added time on manufacturing lead time

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The intersection of lean management and Six Sigma The performance of a business is determined by the complex interactions of people, materials, equipment, and resources in the context of the program that manages these interactions. It is fair to say that management theory regarding operating systems is still evolving. While both Six Sigma and lean management represent the state-of-the art, each system gives priority to certain facets of organizational performance. Therefore, in a highly competitive environment, diminishing returns may result when either program is implemented in isolation. A thorough analysis of the two programs provides some likely reasons why the programs alone may fail to achieve absolute perfection. Figure 5 summarizes the nature of improvements that may occur in organizations that practice lean management or Six Sigma, and the corresponding improvements that an integrated program could offer. The horizontal axis represents the customer’s perspective of value, including quality and delivery performance. The vertical axis represents the producer’s cost to provide the product or service to the customer. Under either system, improvements will be made, but these improvements will begin to level off at a certain point in time. With Six Sigma alone, the leveling off of improvements may be due to the emphasis on optimizing measurable quality and delivery metrics, but ignoring changes in the basic operating systems to remove wasteful activities. With lean management alone, the leveling off of improvements may be due to the emphasis on streamlining product flow, but doing so in a less than scientific manner relating to the use of data and statistical quality control methods. Conclusions A lean, Six Sigma (LSS) organization would capitalize on the strengths of both lean management and Six Sigma. A LSS Organization would include the following three primary tenets of lean management: (1) It would incorporate an overriding philosophy that seeks to maximize the value-added content of all operations.

Figure 5. Nature of competitive advantage

(2) It would constantly evaluate all incentive systems in place to ensure that they result in global optimization instead of local optimization. (3) It would incorporate a management decision-making process that bases every decision on its relative impact on the customer. A LSS organization would include the following three primary tenets of Six Sigma: (1) It would stress data-driven methodologies in all decision making, so that changes are based on scientific rather than ad hoc studies. (2) It would promote methodologies that strive to minimize variation of quality characteristics. (3) It would design and implement a company-wide and highly structured education and training regimen.

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Shingo, S. (1986), Zero Quality Control – Source Inspection and the Poka-yoke System, Productivity Press, Cambridge, MA. Sower, V.E., Savoie, M.J. and Renick, S. (1999), An Introduction to Quality Management and Engineering, Prentice-Hall, Upper Saddle River, NJ, pp. 33-45. Truby, M. (2000), “Nasser, Ford embrace data-driven quality plan”, Detroit News, 26 January, p. F1. Womack, J.P. and Jones, D.T. (1996), Lean Thinking, Simon & Schuster, New York, NY, pp. 90-8. Wong, A. and Hammond, J.H. (1991), Dore´-Dore´, Harvard Business School Publishing, Cambridge, MA.